How can I identify a ROI that is formed by many contours (canny image)? (OpenCV and Python)

I'm newbie with OpenCV, but I'm tring to do a solution to identify flaws in a machining process in a specific Region of Interrest (ROI).

I wrote a code that can 'identify' this ROI and ignores the rest of the part, however I don't know how to create a filter in that region, because my Canny image is formed by a lot of small areas, and not by a single area.

What I want to do, is find a way to get ROI's bounding box (x,y,w,h) coordinates for after filter my input (webcam) image with this ROI and apply again the Canny method to identify this machining flaws

I put my code and a image from the metal part and the Canny image showing the ROI. I've never use computer vision so I'd be very grateful if someone helps me.

def getContours(img):
contours, Hierarchy = cv2.findContours(img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
for i in contours:
    area = cv2.contourArea(i)
    # print(area)
    if area>500:
        cv2.drawContours(img, i, -1, (255, 0, 0), 3)

return img


def empty(a):
    pass


def detect_cont(img, pos_min, pos_max):
    imgGray = convert_gray(img)
    imgBlur = cv2.GaussianBlur(imgGray,(7,7),1)
    imgContours = img.copy()
    imgCanny = cv2.Canny(imgBlur, pos_min, pos_max)  # 200,0

imgContours = getContours(imgCanny)

return imgCanny, imgContours

#cv2.imshow("Image", imgBlur)
#cv2.imshow("ImageCanny", imgCanny)
#cv2.waitKey(0)


if __name__ == '__main__':

#use_webcam()
#img = reading_image("Bad1.jpg")
#reading_video("")

#detect_cont(img)
cv2.namedWindow("TrackBars")
cv2.resizeWindow("TrackBars", 640, 240)
cv2.createTrackbar("Min", "TrackBars", 50, 300, empty)
cv2.createTrackbar("Max", "TrackBars", 50, 300, empty)

cv2.namedWindow("preview")
vc = cv2.VideoCapture(cv2.CAP_DSHOW)
vc.set(cv2.CAP_PROP_FRAME_HEIGHT, 240)
vc.set(cv2.CAP_PROP_FRAME_WIDTH, 320)
vc.set(cv2.CAP_PROP_FOURCC, 0x32595559)
vc.set(10, 150)
vc.set(cv2.CAP_PROP_FPS, 20)

if vc.isOpened():  # try to get the first frame
    rval, frame = vc.read()
else:
    rval = False

running, frame = vc.read()

good = 1
bad = 1

while rval:
    cv2.imshow("preview", frame)

    pos_min = cv2.getTrackbarPos("Min", "TrackBars")
    pos_max = cv2.getTrackbarPos("Max", "TrackBars")

    img_final, imgContours = detect_cont(frame, pos_min, pos_max)
    #cv2.imshow("Tons de Cinza", img_final)
    cv2.imshow("Densenhado", imgContours)

    rval, frame = vc.read()
    key = cv2.waitKey(20)

    if key == 27:  # exit on ESC
        break

    if key & 0xFF == ord("q"):
        running = False

vc.release()
cv2.destroyWindow("preview")

source https://stackoverflow.com/questions/72353750/how-can-i-identify-a-roi-that-is-formed-by-many-contours-canny-image-opencv

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